关键词: 聚类, 变异, 粒子群算法

Abstract: Clustering can be regarded as the process of finding K optimal centers.A group of centers can be seen as a particle，and the inverse of the sum of scatter within class as optimal function，and then mutation probability is used as the condition of particle variation，so as to improve the ability of exploring and overcoming the shortcomings of the particle swarm converging to local optimization value.So the optimal cluster center can be found through mutation particle swarm optimization.The experiment shows that the clustering result of this algorithm is improved and it has good stability.

Key words: clustering, mutation, particle swarm optimization algorithm